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DBMS > Databricks vs. DolphinDB vs. Drizzle vs. FatDB vs. TimescaleDB

System Properties Comparison Databricks vs. DolphinDB vs. Drizzle vs. FatDB vs. TimescaleDB

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDolphinDB  Xexclude from comparisonDrizzle  Xexclude from comparisonFatDB  Xexclude from comparisonTimescaleDB  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A .NET NoSQL DBMS that can integrate with and extend SQL Server.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelDocument store
Relational DBMS
Time Series DBMS
Vector DBMS
Relational DBMSDocument store
Key-value store
Time Series DBMS
Secondary database modelsRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score2.72
Rank#100  Overall
#8  Time Series DBMS
#5  Vector DBMS
Score4.06
Rank#73  Overall
#5  Time Series DBMS
Websitewww.databricks.comwww.dolphindb.comwww.timescale.com
Technical documentationdocs.databricks.comdocs.dolphindb.cn/­en/­help200/­index.htmldocs.timescale.com
DeveloperDatabricksDolphinDB, IncDrizzle project, originally started by Brian AkerFatCloudTimescale
Initial release20132018200820122017
Current releasev2.00.4, January 20227.2.4, September 20122.15.0, May 2024
License infoCommercial or Open Sourcecommercialcommercial infofree community version availableOpen Source infoGNU GPLcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C#C
Server operating systemshostedLinux
Windows
FreeBSD
Linux
OS X
WindowsLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesnoyes
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLSQL-like query languageyes infowith proprietary extensionsno infoVia inetgration in SQL Serveryes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
JDBC.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesPython
R
Scala
C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
C
C++
Java
PHP
C#.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesnoyes infovia applicationsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnono infohooks for callbacks inside the server can be used.yes infovia applicationsyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesMulti-source replication
Source-replica replication
selectable replication factorSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAdministrators, Users, GroupsPluggable authentication mechanisms infoe.g. LDAP, HTTPno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksDolphinDBDrizzleFatDBTimescaleDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksDolphinDBDrizzleFatDBTimescaleDB
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